Quantitative Proteomics and Data Analysis
Laurent Gatto
Quantitative Proteomics and Data Analysis
Laurent Gatto – https://lgatto.github.io
Acknowledgements BBSRC for funding; Sebastian Gibb and Lisa Breckels for coding.
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What is data analysis
The ability to prepare and explore data, identify patterns (good and pathological ones) and convince oneself that the pattern are genuine (rather than random).
To analyse data, you need
Programming skillsBe a statistician/machine learner
To analyse data, you need
Programming skillsBe a statistician/machine learner- Knowledge about the domain
- Know about your data
- Be able to manipulate/visualise it
- How good do we need to be? Good enough!
Data analysis
Definitions
Variability: technical vs biological
Replicates: …
Normalisation: remove unwanted (technical) variation while retaining biological variability.
(see also stats course)
Visualisation
A picture is worth a thousand words.
Graphics reveal data.
Data analysis basics
- Storing data as computational objects (rigorously defined data structures): knowing where to find things
- Application programming interface
- Tidy data: consistency in data structures (and conventions)
The MSnSet class for quantitative data
- Expression/quantitative data
- Feature meta-data
- Sample meta-data
- Dimension constrains
